{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# PyTorch qGAN Implementation\n",
    "\n",
    "\n",
    "## Overview\n",
    "\n",
    "This tutorial introduces step-by-step how to build a PyTorch-based Quantum Generative Adversarial Network algorithm.\n",
    "\n",
    "The tutorial is structured as follows:\n",
    "\n",
    "1. [Introduction](#1.-Introduction)\n",
    "2. [Data and Represtation](#2.-Data-and-Representation)\n",
    "3. [Definitions of the Neural Networks](#3.-Definitions-of-the-Neural-Networks)\n",
    "4. [Setting up the Training Loop](#4.-Setting-up-the-Training-Loop)\n",
    "5. [Model Training](#5.-Model-Training)\n",
    "6. [Results: Cumulative Density Functions](#6.-Results:-Cumulative-Density-Functions)\n",
    "7. [Conclusion](#7.-Conclusion)\n",
    "\n",
    "## 1. Introduction\n",
    "\n",
    "The qGAN \\[1\\] is a hybrid quantum-classical algorithm used for generative modeling tasks. The algorithm uses the interplay of a quantum generator $G_{\\theta}$, i.e., an ansatz (parametrized quantum circuit), and a classical discriminator $D_{\\phi}$, a neural network, to learn the underlying probability distribution given training data.\n",
    "\n",
    "The generator and discriminator are trained in alternating optimization steps, where the generator aims at generating probabilities that will be classified by the discriminator as training data values (i.e, probabilities from the real training distribution), and the discriminator tries to differentiate between original distribution and probabilities from the generator (in other words, telling apart the real and generated distributions). The final goal is for the quantum generator to learn a representation for the target probability distribution.\n",
    "The trained quantum generator can, thus, be used to load a quantum state which is an approximate model of the target distribution.\n",
    "\n",
    "**References:**\n",
    "\n",
    "\\[1\\] Zoufal et al., [Quantum Generative Adversarial Networks for learning and loading random distributions](https://www.nature.com/articles/s41534-019-0223-2)\n",
    "\n",
    "### 1.1. qGANs for Loading Random Distributions\n",
    "\n",
    "Given $k$-dimensional data samples, we employ a quantum Generative Adversarial Network (qGAN) to learn a random distribution and to load it directly into a quantum state:\n",
    "\n",
    "$$ \\big| g_{\\theta}\\rangle = \\sum_{j=0}^{2^n-1} \\sqrt{p_{\\theta}^{j}}\\big| j \\rangle $$\n",
    "\n",
    "where $p_{\\theta}^{j}$ describe the occurrence probabilities of the basis states $\\big| j\\rangle$.\n",
    "\n",
    "The aim of the qGAN training is to generate a state $\\big| g_{\\theta}\\rangle$ where $p_{\\theta}^{j}$, for $j\\in \\left\\{0, \\ldots, {2^n-1} \\right\\}$, describe a probability distribution that is close to the distribution underlying the training data $X=\\left\\{x^0, \\ldots, x^{k-1} \\right\\}$.\n",
    "\n",
    "For further details please refer to [Quantum Generative Adversarial Networks for Learning and Loading Random Distributions](https://arxiv.org/abs/1904.00043) _Zoufal, Lucchi, Woerner_ \\[2019\\].\n",
    "\n",
    "For an example of how to use a trained qGAN in an application, the pricing of financial derivatives, please see the\n",
    "[Option Pricing with qGANs](https://qiskit-community.github.io/qiskit-finance/tutorials/10_qgan_option_pricing.html#) tutorial.\n",
    "\n",
    "## 2. Data and Representation\n",
    "\n",
    "First, we need to load our training data $X$.\n",
    "\n",
    "In this tutorial, the training data is given by a 2D multivariate normal distribution.\n",
    "\n",
    "The goal of the generator is to learn how to represent such distribution, and the trained generator should correspond to an $n$-qubit quantum state\n",
    "\\begin{equation}\n",
    "|g_{\\text{trained}}\\rangle=\\sum\\limits_{j=0}^{k-1}\\sqrt{p_{j}}|x_{j}\\rangle,\n",
    "\\end{equation}\n",
    "where the basis states $|x_{j}\\rangle$ represent the data items in the training data set\n",
    "$X={x_0, \\ldots, x_{k-1}}$ with $k\\leq 2^n$ and $p_j$ refers to the sampling probability\n",
    "of $|x_{j}\\rangle$.\n",
    "\n",
    "To facilitate this representation, we need to map the samples from the multivariate\n",
    "normal distribution to discrete values. The number of values that can be represented\n",
    "depends on the number of qubits used for the mapping.\n",
    "Hence, the data resolution is defined by the number of qubits.\n",
    "If we use $3$ qubits to represent one feature, we have $2^3 = 8$ discrete values.\n",
    "\n",
    "We first begin by fixing seeds in the random number generators for reproducibility of the outcome in this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "from qiskit_machine_learning.utils import algorithm_globals\n",
    "\n",
    "algorithm_globals.random_seed = 123456\n",
    "_ = torch.manual_seed(123456)  # suppress output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "We fix the number of dimensions, the discretization number and compute the number of qubits required as $2^3 = 8$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "num_dim = 2\n",
    "num_discrete_values = 8\n",
    "num_qubits = num_dim * int(np.log2(num_discrete_values))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, we prepare a discrete distribution from the continuous 2D normal distribution. We evaluate the continuous probability density function (PDF) on the grid $(-2, 2)^2$ with a discretization of $8$ values per feature. Thus, we have $64$ values of the PDF. Since this will be a discrete distribution we normalize the obtained probabilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import multivariate_normal\n",
    "\n",
    "coords = np.linspace(-2, 2, num_discrete_values)\n",
    "rv = multivariate_normal(mean=[0.0, 0.0], cov=[[1, 0], [0, 1]], seed=algorithm_globals.random_seed)\n",
    "grid_elements = np.transpose([np.tile(coords, len(coords)), np.repeat(coords, len(coords))])\n",
    "prob_data = rv.pdf(grid_elements)\n",
    "prob_data = prob_data / np.sum(prob_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize our distribution. It is a nice bell-shaped bivariate normal distribution on a discrete grid."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "\n",
    "mesh_x, mesh_y = np.meshgrid(coords, coords)\n",
    "grid_shape = (num_discrete_values, num_discrete_values)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(9, 9), subplot_kw={\"projection\": \"3d\"})\n",
    "prob_grid = np.reshape(prob_data, grid_shape)\n",
    "surf = ax.plot_surface(mesh_x, mesh_y, prob_grid, cmap=cm.coolwarm, linewidth=0, antialiased=False)\n",
    "fig.colorbar(surf, shrink=0.5, aspect=5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 3. Definitions of the Neural Networks\n",
    "In this section we define two neural networks as described above:\n",
    "\n",
    "- A quantum generator as a quantum neural network.\n",
    "- A classical discriminator as a PyTorch-based neural network.\n",
    "\n",
    "### 3.1. Definition of the quantum neural network ansatz\n",
    "\n",
    "Now, we define the parameterized quantum circuit $G\\left(\\boldsymbol{\\theta}\\right)$ with $\\boldsymbol{\\theta} = {\\theta_1, ..., \\theta_k}$ which will be used in our quantum generator.\n",
    "\n",
    "To implement the quantum generator, we choose a hardware efficient ansatz with $6$ repetitions. The ansatz implements $R_Y$, $R_Z$ rotations and $CX$ gates which takes a uniform distribution as an input state. Notably, for $k>1$ the generator's parameters must be chosen carefully. For example, the circuit depth should be more than $1$ because higher circuit depths enable the representation of more complex structures. Here, we construct quite a deep circuit with a large number of parameters to be able to adequately capture and represent the distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from qiskit import QuantumCircuit\n",
    "from qiskit.circuit.library import efficient_su2\n",
    "\n",
    "qc = QuantumCircuit(num_qubits)\n",
    "qc.h(qc.qubits)\n",
    "\n",
    "ansatz = efficient_su2(num_qubits, reps=6)\n",
    "qc.compose(ansatz, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Let's draw our circuit and see what it looks like. On the plot we may notice a pattern that appears $6$ times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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96667tHbtWk2bNs35+6mnntIPP/ygyZMnKykpSe3bt1eiK5Wa5vzckx56+qHd6fudn6X/Wi4j86Bqlq2oHy64T5sGvqmP+w7UExO/cjrK3KZutebq3KK3urXso4t7DdK/r/5Of66arOe/uFFuEuk+YCqXKqubOp2if/W8qJi2Eii+xNmXf/HPLpUzWSbAZm61GVw/HF/8SWiFMXmpdOBgDN53if9zTVReqAuoB7KzxPk3RoVOnA2wWRRf/FlaskEJw2LahIXF/74241wsBuijxQsxwBAHstfzr/7q329zawtYEuqIudI7Y3NfJh5NW+6/mKa4TV/un7kvUXkhDhADspu1UnptZOjE2YDVW6WXfpH+XKuEYXWyJbDFgl18lKi8EAMMcSB7gunro6SxCw5PnA2wJPQxf0pvjM59mXhkFwTv3Beb97W7YCQq4oD34gAAAAAAAIBnk2cHDhyoVatW6dZbb9Wzzz6r8uXLZz03aNAgdejQQRkZGWrUqJEqVEjQaTOCNK5Y3fk5f8vqkM/P3+z/f6O/liubVkqP9LxIzSrXUnJSsjrWaKQzm3bRb6v/lNu1adRDvTv316iZQzRn2W9yi0j3AdO7UTtd3LKHGlRIsGl2gHx8+Ju00j+5eFgJKMNnKaFm0oxVEpLd7tot3FgXUA8cYsf/RxPCS4y3ffvN0dKOBBkEXrstdgPWsYo/RcGNMcAQBw4ZMlFauim8ZZ2Z52YoYcTqWLQEI7tds1u4MQ4QAw6xhNn3xoeXGG8Jc2+PkbbsUkLYtNP/iAXaAvGPOHCIzTptMyaHwxLov56qhDEvRgn/dn61IIEuNsgPccD9cQAAAAAAAMCTybPz5s3TkCFDVK1aNT3xxBMhl+nSpYvz05JoAz7//HOdf/75atiwocqUKaOWLVvq/vvv165d8T+C0qlmY9UvX1Wfzp+gNbu2ZnvuwMEMvTp9uJKUpDOb+cudU/rBDI1bPV/tqjeQF/Tr/YCSk1P03rAH5RaF3QcAt7DEMkuCicToP/2zzyXCLFPhJgUXhVUxfO+i4La6gHrgkFHzIptFcs+BxJlVNZYxYM22xJqRy2sxwBAH/CypzGZJjcS4BbGZzTXR6mPaAvGNGHDI6PmR1Vl2Mc24BJlVNZZtgY07EvtuFG6PAYY44GcXm01aHNlrJiyOzWyuBbFqszdjUFEgDgAAAAAAAHhXqlzqk08+UWZmpvr166dy5cqFXKZ06dKHJc/aDLUNGjTQ448/rnr16mnGjBl65JFHNHr0aI0ZM0bJyfGbb5yanKIXe1+jC795Tl3eu1dXte2lppVqaP2e7fps/kTN3bxK9x51to6oUifk62//9V2VL1Fal7c5Vl5Qt1oz9epwiX6d/pFmLRmrdk0Sv9yF3QcAtyjILUwtWcZmoD26qeLatj3SrhgO5rltkMxtdQH1gJ8NeM9YUbDbEPduI6XEb3Mv5sehJSTbBQr1q8oV3BYDDHHA77dFUhgTT2dz4KA0eal03BGKa7v3S5tjeG3nCtoCcY0YcKhtP3Vp5K+zRLs+7aUSKYprsWwLWGxdvUVqWlOu4LYYYIgDfhMXhXcXipxtXYsDdk4Qz+zC33U7Yvf+9AvEP+IAAAAAAACAx5NnR4wY4fzs1atXrsusWrXqsOTZ7777TtWrH7pd0fHHH+/8bUm448aN03HHHad4dnrTThp96cN6dvJ3+nDOGG3et0tlS5RUxxqN9FH3gbqw5dEhX3fPyA80cc1CDb/ofqWluHa3OMylJ92vkTM+0XvDH9SzN46UGxR0HwDcxG63WNDXJULyrJffvyi4rS6gHpCWbIhs1tng2anWb5fqVFZc2x4HccAtybNujAGGOFDw2wlbWyDek2djHQNi/f5FwW1xgBggLdvkT4gvSHL66q1Sozi/Y3Ws2+Sxfv9oc1sMMMSBwvULxHvy7I69/rvSxIrbYoAhDgAAAAAAAHhTks8Xy662olO/fn0nOXb69Onq2LHjYc9nZGSodu3a2rRpkxYvXqwmTZrkuq4FCxboiCOO0Mcff6xLL7004m3p2rWr1q1bF9FrSqeU0NyLHldxuGvE+xqxYo6TOFu9TIUCraP1p//Q3oMFv29fWmppvX5rgtwfMUwDXmquAxl7C/Ta4vz+A75ZOFl3j/xACwe8EJN9AIimM+6fqtIVIp8Kae28XzX+3SsVz6o36a7jb/gs5HN3niZV8E+qnqsKpSSbRD0zU9qxL+/BuOeGHv7/bWvm6JfnT1U0uDH2R7NeKO66wE31QMOuF+nIC58r0GtHvnKONi+fonh27LUfqWaL4wsUB8KNAXnFgYkf3ahVf3yvwiIG5I32YOGcds84lavWKOLXbVwyUaMHX6B4Vrlue5008MeYtQV2blqqYc9EZ0Y24oC72gLxFAfqtT9TR/d7rUCvHfvmZVq/cIziWff+b6pu29Ni1haY/NmdWj7lUxUWMSBvtAUKp/ftw1SpTuRZsFtWzdSIF89QPCtfo5lOvWtUrs9HKw7kFgP27livHx7romggDuTNC3HA7h64dq0/293GcWw8BwAAAAAAoLi4dorR3bt3Oz/37g3dGTVkyBAncbZ8+fJq3LhxnusaOdJ/tXmrVq0KtC2WOLt69eqIXlOmREkVh7/9+p5Grpijny/+Z4ETZ82atWu1J31/gV9fqkQZuc3aNWu0L71gUzEU1/dvDmZmKj0zQ+mZB51ZK/ZlHFCSklQytUSx7gNANO3fu7NAybM7t2+KOF4Xt8wyuW+fDY5VCjOc2kBZuMsG27d3d9Q+IzfG/mjWC8VVF7ixHihTz393gYJYs2qpNsV5HNize2eh40BBY4DZuCHytm0oxIC80R4snL27t6lcAWaO3LVjc9y3BfYnV4lpW+DAvj20BVwWB6IVA+IpDpSovrLAr127epnWxnkc2L1re0zbAps3rqct4KIY4Na2wJ5d21SpIK/buTXu2wIV0/PeN4o6DqQf2EdboICIA3lbv359gV4HAAAAAABQUK5Nnq1Vq5a2bt2qadOmqXv37tmesyuZ77nnHuf39u3bKykpKdf1WEfgAw88oNNOOy3kDLbhbkuk7KryorZ8+0a9PH2YSqaUUIs3bs/6f8+6LfXdBfdGtK46tWsXeuZZt6ldp06hZp4tLh/NHavrhg7O+rvCf69SwwrVIp5doLD7ABBN21fNUKWazSJ+3Z6Nc1W3bl3Fs7Kl8p4VJj+RzDATSub+7VH7jNwY+6NZLxRXXeDKemDXcvkyM5VkO3sE9u/eqtJJu+M+DihjV4HjQKSzzYVSNi0zKp8RMSBvtAcLZ8eaP1S9YeTnb7vXz4n7GFCyTHJM2wIHaQu4Lg5EKwbEUxxI3rtGmRkHlJyaFtHrMvbvVtrBLXEfB5Ji3BYoU+IgbQEXxQC3tgV2rp0ltTgm4tftWjc77mNAasm8941oxYHc1pOxdyttgQIiDuQ982zNmpFfCA8AAAAAAFAYST6fXUfsPgMHDtSLL76o+vXr65dfflGLFi2c/0+ePFn9+/fXkiVLlJ6erltuuUUvvfRSyHXs2rVLJ5xwgjNzrL2udu3axbb9vgMZyrg/9G2541HqYxcqKa3gudgHD0gjC35nyLjUa6CUEtk4XcJ+/9HYB4BoWrZJ+u+wyF5TIkV65FypTPFN6lEgVmv/43Np74GCvf7hc/0zy2zbIz38VeSvP7Wd1Ke9osKNsT+a9UKi1QXxVg+8MUqaE+FkSL1aSWd3Vtwb+6f0xZTYxAC75uypi2yQW4VGDHBXDIi3OLBmq/T0j5G9JiVZeuicvG9zHC8e+lLavjc2cSCasZI4kDfiQOG8N06avjyy1/RoLl3UTXHv9yXSxxNiEwPMYxdIZaNw3kQMyBsxoHA27ZQe/Tay19j0Cg+cLVUpp7j32LfSxtxvSFGkcSCasZI4kDcvxAG7g2C5cuWyxmPKli1bhFsHAAAAAACQXWTTcSWQQYMGqWrVqlq5cqXatGmjdu3aqXnz5urWrZuaNGmiE0880VmuQ4cOIV+/d+9e9e3bV0uXLtXw4cOLNXEWAFA4DatKjSK8VfNRTeM/cTaQuFavcuzev37ud4oG4soJLSNbPjVFOqa5EkL9qrF771oVopM4CxS1OpWlFhHeAKRLo8RInDX1qnjzvYFIHN/SnwgXSQL9sf7rruNeLNvkVcpGJ3EWKGrVykvt6kX2mg4NEiNxNtb1Mf0CAAAAAAAAcAvXJs/Wq1dPY8eO1RlnnKFSpUpp2bJlqlKligYPHqwffvhBCxYsyDV51makveCCCzRlyhT99NNPat26dQxKAAAoTILpVcdKlcOcrKJpjcSYbTIg0mSgaLGEgsbVY/PeQKSa15LO6hTesslJUv8e/gH2RGAJ9GUKOLt9ND5XIFH0P0aqHuZx3aCqdP6RShixagtYvGxWIzbvDUTKLqY7r2t4y1qS7SVHSbUrKSHUrBC7ZP9YxR+gIC49WqpdMbxl61SSLj5KCSOWx2LzmrF7bwAAAAAAACCaXJs8a1q1aqXvv/9eO3fudB6TJk3SgAEDnFsBWTJtcnKy2rZtm+01mZmZ6tevn3799Vd98803zky1AIDEY7cgvOMUqUn1vAfJbZa5G3pJJVKUMGyWXEtkLW6dGjLLFBLLia39txMtVSL3ZSqUkq473j/LVKKwWXItDsRCoszOC5jypaSBp+SfXGLH/y0nSSUTaFblIxvHpu3Stp5UsUzxvy9QUMceIfXrnvdFJ+VK+i+8O7KJEkZystS9WWzem7YAEondXea2k6XWdfJerk1d6daTpdIxukCtIDo3yvs8p6i0rJ04Fx0CAAAAAAAA+Umg4cHomTNnjnw+n1q0aKEyZbKP/N1yyy367LPP9Pe//915buLEiVnPNW3aVNWrM+UeACQKS+6wpJmVm6VxC6XJS6RMn3/WtF6tpB7NpaoJckvGYDbLVPv60vTlxfu+PRPkNrZAMDvOuzSWpi3zx4Blm/xxIDVZuryH1K5+bJLRo5G4MnJe8c8wVTPMmbuAeEqgvfkkafVWadwCadLiQ22B447wH0vVKyghk4HsAqCJi4v3fWkLIBFZUqwlyVvb+fcl0tKN/jhg9f9lR/ufswtTEo0lz/4821+W4tKwqlS/avG9HxCtOnNAL2nddmn8Amn8wkNtgWNa+NsCtRKwjWsX/XRrIo35s3jfl7YAAAAAAAAA3CQBUwUKb9asWc7PDh06HPbcTz/95Px88skn1b1792yPH374odi3FQBQeDbAa7drtAQaYz/7dkrMxNmAU9oWb8KfzdRjg+VAIrKBZUswsWT6QBywWZQ7NkzMxFljsz3ZYHlxOq198b4fEE11K/tvxRzcFjinS2Imzgb0blO8s882rcFtmpG40lL9s7bbDJSBOGAzztoFNomYOBu404ZdJFScaAsgkVmC7PlHZm8LnN81MRNnA+yi4OKcOb9B1fxn8QUAAP/P3n2AR1Hnfxz/pJJOS+i99y5dBQQV7AhYEHsvyIn1vPP8e55d7+yAvYsFOyJKky5dem8hoQcICSH1//xmCEVCyG42W2bfr+fZJ2XLzCY7n/3tzHe+PwAAAACBJCg7zxZXPLtp0yYFqrVpqbrp51HafShd5SNj9Hb/29UysZYC1fqUJfrvV7co83C6qlaoq4eu+kgV4pLU74EQ1avWSjcPeFZdmg9Qdk6W/vPJldq8Y4XKRUSrQlwVDR/4pmom2nMY3j+qtzakLNE1/R7TwDNHlGqdfv/zK81d+ZMOHko75fIAwBuqV5DOay2NX1L2yzJTQQ7pIoWE+E/2G69/O1yzV3yvHWmb9eaIRWpUs91Jjzdh3nt68Ysb9fh136hHq0ut3/G+AKcwhX+rU6X9h8p+WaZDpymcC5TxX3buYY3+YaTmr/lFkeFRali9rR6++mPrOjIATmGK6C9sJ32zwDuFh+ZEJH8bCzw05lylpW9XSEioYqLiddclr6hRzfbWdXNXjtf7v/xD+fn5ys/P1eBeD+jcTtdZ15EDcIqL2kkrU6Q9B8t+WV0bSs1r+FcGXPNUPUWEl1NkeLT181V9HlGvdldY3yfvWqvnx16n/Rm7FRtVXg9c8b7qVWtpXUcGwCkqxtqfCcbOLftlWd26u0mhof6VA6ca97O/GAAAAAAAACVB8ayD3DXxHd3cpo+ubXW2vl49Vzf/PEqzhz2pQPX82Ot1/5D3rGKoCX+8qzE/3q8Hr/zAuu6/d05XXHSFo7cd0OVWdW7WXyEhIfp25mt66cub9eIdU63rXrh9ip77/HqPrNPMZd/o7DZDFBYWccrl+dKSnZt1x8S3lJ6dpboJiXpvwJ1asTtZF417Vk0q1tD4QQ+rSmx5q9D6zonvKC0rQ1l52RpQv72e6XW1QkNC9fL88Rq1+FfFRkRp/nVP+/opASjGOS2kZcnSlj0lv8+BQyd+LYmBnezOVv6W/We2GaQhvR7U397oWeRjbd+7ST/PfUvN63Q94fdOel8oae7/Y/rn+nbtPJULi1BEaJie6DlE59a3x0H5Bfm6b/KHmrBhsbX+93Q4X3d2OM+6jvcE/xYTaXfSHDO1bDMgKV664OTadL8e/70z/mHr9+8/uMb6uvfAdkdmgCs58M/pY/Xj+oUKC7ErHh7ocpGuaNbd+r64jCAH/NuZTaU/t0rrd5ZtDlzc3i7W9bcc+OewL47+PGPpN9Z9R9+3RAUFBXr2s2v0wu1T1aBGG2tMcOPzzdSz1UCryNZJOVDSDCi0cs82df3oUWvfwYt9rj3hsXZm7FeHDx5SlxqN9fWlI63ffbFqtp6cNU6pGWnadc/bZf584JpyEdKVXaU3JkkFBWWXARVjpEs6yO8ywHh06NgiT6J7+evbrLHCeWdcbxW2mcd9/d551nVOygBXcsCccD9p81IlRttt1/vWbaVneg09+jijFv2q1xf9ovDQMIWGhGjm0CcUFR6ph6d+oi9Xz1G7qvWOZgP8hylsN2MBU0hfUu7kwAVtvdel15UcKG7cHyz7i10ZC5xqO2dfMQAAAAAACFZBWTw7efJkOY05yLVgx0aNH/yI9fPAJp01YtL7Wpe2XY0qVjvl/fZlZaj9+w/pUG62asVX1uG8HG3cv1NDW/TU6PNula+s27ZI0eXijh4A6dfpOo3+caRycrNPum1kRNTRbgOGKZL6atoLLi/z4KF9uuXFVjqcc0hJ5WsrJ++wtu/ZoHM6DtPIwW8rNy9HyzfNtLqVhIdFlHp5ZeHmCaP01vm3qV2Venp/6VQ9NPUTXdfqbGtH6fE7Nx+e9qkuadxJd3c4X1m52er28T/Ve+MS9W/QXvd2GmDdf+SUj3z6XACUrPPLLWdLr/wq7Uov2X1emuDaMkx3W29NDe9K9httGpx1yscyXebMgaq7Ln3V6kLjjkB4Xyhp7ves2UyPdh2o6IhI68DaOZ8/oc23v67YyCh9smKGVUiz/KaXtP9wpjp/+HedXael1b2e9wT/16KmPd3s1/PLJgPKR0u39/HOdLCeGv8dys7QhD/e0af/SLYOXBuVEk49Hg7kDHAlB0aecaH+fabdjW9b+l61ee8BnVOnlRJjEorNCHLAv4WGSDeeJb32q5S6v2xywEwJ3aOxf44Fji+eycgyf4DjWuOGhOhg1j7r28ysA0qIqWx1qHRaDpQ0A4ycvFzdOfFt67NgUe789R0NaNBBe7KODSyHNOumztUb6YwP7X0N8D+Nq0pXdpE+m1M2GRBbzh4LREfK7zLgVNIO7tSa5Pl65paJ1s9ntr5cr31zt7btXudSF8hAyABXc+C+My7U8I79T3qM79fN12crZ2rG0CdUvlyMdmUeUESoPQA0BbYtEmvpu3UlHHDCq8xw97qe0uu/SVv3lk0OdG9sjwe8wZUcKG7cH0z7i0uaAcVt5+wrBgAAAAAAwSooi2edKDl9j6rFVrDOGjfMDsPaCZW1NX1PscWzFaJidUXz7oqPjNKj3QZq4sYlenbudz4tnDVS927UxtSluu2lY91DDmdnaveBbae97zczXla3lpe4vExz4LVPu6sVXS5e1/T7p+at/kWfTX7K2hFqLF43RS3qdj9hR2hpludpi3ZsUlxElLUz0xjW8iw9OPVjXdWix0m3DVGIVSBlmMLpnPxcVYut6PV1BlB68dHS3f2kNydJ20tYNFNS/dtI57ZSQGT/X339+0tqWa+HmtTq6Pb6+Pv7giu5f36DY3/T1km1ZRqT7TqUbhXGfbVqjm5s01thoaGqFB2nQc26auyqWVbnSQRO50lzrPjrebL+t56cBvbOc6TKcQqo8V/q7vWKj6lkba8L1/5mTZs6rN/j6tD4HEdlgKs5YMb9hQ7mZFmdOfOPtCksLiPg/0xh2119pVFTpOQSFs240uX+wnZ2xvhrDjz72bVasn6K9f1/bhp/9PPwP4aO1f99MFBRkbHWNMr/unacIsIjHZUDrmSA8eTscbq8aRftPXTw6OfBQu8tnaL65ZPUOqkOBXIBqEtDezs1BbQl7UBb0pNo7jhHqlrefzPguc+vVYEK1Kx2Z9004Blravdd+7aqUkJ1hYWFH82EKhXraOe+LS4Vz/p7BriTA6fy0rwf9Y/uA62COiMpxu5Oi8AQFSHd0ceekWLTbs9/1riso3+OBVwZ9zt1f7ErGVDcds6+YgAAAAAAEKwonoX+3LlZdx2Znnnhjo1Hd7b5WrM6XfTMLb8c/XnQ40mnvc+nk55Syu51eu62SW4tc13KYl3Wc7j1/drkBWpUo/3R62Yt/1Y9Wl3m0eV50qb9O7Vs91Z1+uBYR6DM3GylpJ98BP3F3sN02TcvaMzi35R2OEN/73qZ2lf1j/87APcOao84T/p+oTRrXekfLyFKGtJFalVLAZH9f7Vx+zJNX/q1Xrrz91Kvjz+/L7iS+8f7YNk01S9fxZrO0diSvufo90a9hCTNTV1bhmuOstCziVQ1Qfp8rrTnYOkfr31du6NtXFTgjf/y8nO1I22z6lZpoZsHPGN1r3poTD+9ff9yVYyv6pgMcCcHXls4QW8u+tXqPDvqvFtOmMr9VBmBwGC21eH9pB8XS9NXl76Q3hTkDj5DaldXXudqDjx01YfW14nzP9Bb4x/SUzeNV15erj6Z9KT+dd04q1P96q3z9Nh7F2vMyKUqH5vomBxwJQP+SF2nuSlr9fPgv+vfs74+4bqN+3ZqzOJJmnzlY/py9ewyX2+UDTNbRFK89Onsks9KUZzWtaTBnaWEaPltBrx0x+9WUazp/PjehH/oubHXWRngSf6cAW6NBRZMsDpT1klI1OM9Bx/dB2hmoliwfYOenDXOmpXqmpZnWh0oEThijpxM8/Of0pSVpS+kN92mB3aUOtX3XuGsqzlQ0nG/k/cXu5IBxW3n7CsGAAAAAADBiuJZh6gVX1nbM/YpNz/P6j5rOkltPbBHteMrn/a+ZmrWwp3lpnj2wobud+nzlOqVGlgdQQplZB1QVnaGEhNqnvI+X059QTOWjdNzt/6mqEj7DHpXbUhZrEY12x/dGdqt5cXW9+bvOX/1L7rlguc8ujxP61y9oX4adGxnaY3XbyvydqMW/2Z1HH6oyyXambFf/b54Up2qNVTfeq29uLYAPN1pxhS8tq0jfTXPvQPmZupnc2Dskg520UwgZH9Rlm2Yrh1pm3T9s/Yc03vTt+t/X92qvQdSdVH3Oxz1vlDS3C80efMy60DZ+MGPHJ3WEs7RuJr04ADpxyXSrLXmYLLrj1ExRrq0o50lgTr+M0U0oSGh6tNhqPWz2YarVapvdbBytXjW3zPA1RwwB8fNxYz/rx//hvrVa63K0fFHrycjAltkuDSwk9S2tvTlPPc60pt/e/s60mWdpPiowBoLnNvpOr389e06kLHH6lq350CKVThrNK19hhLL17KKajo26eeoHChJBmTmHNY9v72rzy8acdK2bZ7Hrb+M0ct9r1d0hGudeeF/6idJDwywi+dmrJFy8tw7Me/iDlKHut4vmHM1A8x7vmE6Pg48c4RueK6J9XNShdrW2N8U0pvus+Z1vjNti6pUcH2A4+8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      "text/plain": [
       "<Figure size 2210.55x1120.39 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc.decompose().draw(output=\"mpl\", style=\"clifford\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's print the number of trainable parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "84"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc.num_parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### 3.2. Definition of the quantum generator\n",
    "\n",
    "We start defining the generator by creating a sampler for the ansatz. The reference implementation is a statevector-based implementation, thus it returns exact probabilities as a result of circuit execution. In this case the implementation samples probabilities from the multinomial distribution constructed from the measured quasi probabilities. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.primitives import StatevectorSampler as Sampler\n",
    "\n",
    "sampler = Sampler()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we define a function that creates the quantum generator from a given parameterized quantum circuit. Inside this function we create a neural network that returns the quasi probability distribution evaluated by the underlying Sampler. We fix `initial_weights` for reproducibility purposes. In the end we wrap the created quantum neural network in `TorchConnector` to make use of PyTorch-based training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from qiskit_machine_learning.connectors import TorchConnector\n",
    "from qiskit_machine_learning.neural_networks import SamplerQNN\n",
    "\n",
    "\n",
    "def create_generator() -> TorchConnector:\n",
    "    qnn = SamplerQNN(\n",
    "        circuit=qc,\n",
    "        sampler=sampler,\n",
    "        input_params=[],\n",
    "        weight_params=qc.parameters,\n",
    "        sparse=False,\n",
    "    )\n",
    "\n",
    "    initial_weights = algorithm_globals.random.random(qc.num_parameters)\n",
    "    return TorchConnector(qnn, initial_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### 3.3. Definition of the classical discriminator\n",
    "\n",
    "Next, we define a PyTorch-based classical neural network that represents the classical discriminator. The underlying gradients can be automatically computed with PyTorch."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from torch import nn\n",
    "\n",
    "\n",
    "class Discriminator(nn.Module):\n",
    "    def __init__(self, input_size):\n",
    "        super(Discriminator, self).__init__()\n",
    "\n",
    "        self.linear_input = nn.Linear(input_size, 20)\n",
    "        self.leaky_relu = nn.LeakyReLU(0.2)\n",
    "        self.linear20 = nn.Linear(20, 1)\n",
    "        self.sigmoid = nn.Sigmoid()\n",
    "\n",
    "    def forward(self, input: torch.Tensor) -> torch.Tensor:\n",
    "        x = self.linear_input(input)\n",
    "        x = self.leaky_relu(x)\n",
    "        x = self.linear20(x)\n",
    "        x = self.sigmoid(x)\n",
    "        return x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4. Create a generator and a discriminator\n",
    "\n",
    "Now we create a generator and a discriminator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No gradient function provided, creating a gradient function. If your Sampler requires transpilation, please provide a pass manager.\n"
     ]
    }
   ],
   "source": [
    "generator = create_generator()\n",
    "discriminator = Discriminator(num_dim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 4. Setting up the Training Loop\n",
    "In this section we set up:\n",
    "\n",
    "- A loss function for the generator and discriminator.\n",
    "- Optimizers for both.\n",
    "- A utility plotting function to visualize training process.\n",
    "\n",
    "### 4.1. Definition of the loss functions\n",
    "We want to train the generator and the discriminator with binary cross entropy as the loss function:\n",
    "$$L\\left(\\boldsymbol{\\theta}\\right)=\\sum_jp_j\\left(\\boldsymbol{\\theta}\\right)\\left[y_j\\log(x_j) + (1-y_j)\\log(1-x_j)\\right],$$\n",
    "where $x_j$ refers to a data sample and $y_j$ to the corresponding label.\n",
    "\n",
    "Since PyTorch's `binary_cross_entropy` is not differentiable with respect to weights, we implement the loss function manually to be able to evaluate gradients."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def adversarial_loss(input, target, w):\n",
    "    bce_loss = target * torch.log(input) + (1 - target) * torch.log(1 - input)\n",
    "    weighted_loss = w * bce_loss\n",
    "    total_loss = -torch.sum(weighted_loss)\n",
    "    return total_loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### 4.2. Definition of the optimizers\n",
    "In order to train the generator and discriminator, we need to define optimization schemes. In the following, we employ a momentum based optimizer called Adam, see [Kingma et al., Adam: A method for stochastic optimization](https://arxiv.org/abs/1412.6980) for more details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from torch.optim import Adam\n",
    "\n",
    "lr = 0.01  # learning rate\n",
    "b1 = 0.7  # first momentum parameter\n",
    "b2 = 0.999  # second momentum parameter\n",
    "\n",
    "generator_optimizer = Adam(generator.parameters(), lr=lr, betas=(b1, b2), weight_decay=0.005)\n",
    "discriminator_optimizer = Adam(\n",
    "    discriminator.parameters(), lr=lr, betas=(b1, b2), weight_decay=0.005\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### 4.3. Visualization of the training process\n",
    "We will visualize what is happening during the training by plotting the evolution of the generator's and the discriminator's loss functions during the training, as well as the progress in the relative entropy between the trained and the target distribution. We define a function that plots the loss functions and relative entropy. We call this function once an epoch of training is complete.\n",
    "\n",
    "Visualization of the training process begins when training data is collected across two epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from IPython.display import clear_output\n",
    "\n",
    "\n",
    "def plot_training_progress():\n",
    "    # we don't plot if we don't have enough data\n",
    "    if len(generator_loss_values) < 2:\n",
    "        return\n",
    "\n",
    "    clear_output(wait=True)\n",
    "    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(18, 9))\n",
    "\n",
    "    # Generator Loss\n",
    "    ax1.set_title(\"Loss\")\n",
    "    ax1.plot(generator_loss_values, label=\"generator loss\", color=\"royalblue\")\n",
    "    ax1.plot(discriminator_loss_values, label=\"discriminator loss\", color=\"magenta\")\n",
    "    ax1.legend(loc=\"best\")\n",
    "    ax1.set_xlabel(\"Iteration\")\n",
    "    ax1.set_ylabel(\"Loss\")\n",
    "    ax1.grid()\n",
    "\n",
    "    # Relative Entropy\n",
    "    ax2.set_title(\"Relative entropy\")\n",
    "    ax2.plot(entropy_values)\n",
    "    ax2.set_xlabel(\"Iteration\")\n",
    "    ax2.set_ylabel(\"Relative entropy\")\n",
    "    ax2.grid()\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 5. Model Training\n",
    "In the training loop we monitor not only loss functions, but relative entropy as well. The relative entropy describes a distance metric for distributions. Hence, we can use it to benchmark how close/far away the trained distribution is from the target distribution.\n",
    "\n",
    "Now, we are ready to train our model. It may take some time to train the model so be patient."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1800x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fit in 191.31 sec\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "from scipy.stats import multivariate_normal, entropy\n",
    "\n",
    "n_epochs = 50\n",
    "\n",
    "num_qnn_outputs = num_discrete_values**num_dim\n",
    "\n",
    "generator_loss_values = []\n",
    "discriminator_loss_values = []\n",
    "entropy_values = []\n",
    "\n",
    "start = time.time()\n",
    "for epoch in range(n_epochs):\n",
    "\n",
    "    valid = torch.ones(num_qnn_outputs, 1, dtype=torch.float)\n",
    "    fake = torch.zeros(num_qnn_outputs, 1, dtype=torch.float)\n",
    "\n",
    "    # Configure input\n",
    "    real_dist = torch.tensor(prob_data, dtype=torch.float).reshape(-1, 1)\n",
    "\n",
    "    # Configure samples\n",
    "    samples = torch.tensor(grid_elements, dtype=torch.float)\n",
    "    disc_value = discriminator(samples)\n",
    "\n",
    "    # Generate data\n",
    "    gen_dist = generator(torch.tensor([])).reshape(-1, 1)\n",
    "\n",
    "    # Train generator\n",
    "    generator_optimizer.zero_grad()\n",
    "    generator_loss = adversarial_loss(disc_value, valid, gen_dist)\n",
    "\n",
    "    # store for plotting\n",
    "    generator_loss_values.append(generator_loss.detach().item())\n",
    "\n",
    "    generator_loss.backward(retain_graph=True)\n",
    "    generator_optimizer.step()\n",
    "\n",
    "    # Train Discriminator\n",
    "    discriminator_optimizer.zero_grad()\n",
    "\n",
    "    real_loss = adversarial_loss(disc_value, valid, real_dist)\n",
    "    fake_loss = adversarial_loss(disc_value, fake, gen_dist.detach())\n",
    "    discriminator_loss = (real_loss + fake_loss) / 2\n",
    "\n",
    "    # Store for plotting\n",
    "    discriminator_loss_values.append(discriminator_loss.detach().item())\n",
    "\n",
    "    discriminator_loss.backward()\n",
    "    discriminator_optimizer.step()\n",
    "\n",
    "    entropy_value = entropy(gen_dist.detach().squeeze().numpy(), prob_data)\n",
    "    entropy_values.append(entropy_value)\n",
    "\n",
    "    plot_training_progress()\n",
    "\n",
    "elapsed = time.time() - start\n",
    "print(f\"Fit in {elapsed:0.2f} sec\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 6. Results: Cumulative Density Functions\n",
    "In this section we compare the cumulative distribution function (CDF) of the trained distribution to the CDF of the target distribution.\n",
    "\n",
    "First, we generate a new probability distribution with PyTorch autograd turned off as we are not going to train the model anymore."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "with torch.no_grad():\n",
    "    generated_probabilities = generator().numpy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And then, we plot the cumulative distribution functions of the generated distribution, original distribution, and the difference between them. Please, be careful, the scale on the third plot **is not the same** as on the first and second plot, and the actual difference between the two plotted CDFs is pretty small."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x900 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(18, 9))\n",
    "\n",
    "# Generated CDF\n",
    "gen_prob_grid = np.reshape(np.cumsum(generated_probabilities), grid_shape)\n",
    "\n",
    "ax1 = fig.add_subplot(1, 3, 1, projection=\"3d\")\n",
    "ax1.set_title(\"Generated CDF\")\n",
    "ax1.plot_surface(mesh_x, mesh_y, gen_prob_grid, linewidth=0, antialiased=False, cmap=cm.coolwarm)\n",
    "ax1.set_zlim(-0.05, 1.05)\n",
    "\n",
    "# Real CDF\n",
    "real_prob_grid = np.reshape(np.cumsum(prob_data), grid_shape)\n",
    "\n",
    "ax2 = fig.add_subplot(1, 3, 2, projection=\"3d\")\n",
    "ax2.set_title(\"True CDF\")\n",
    "ax2.plot_surface(mesh_x, mesh_y, real_prob_grid, linewidth=0, antialiased=False, cmap=cm.coolwarm)\n",
    "ax2.set_zlim(-0.05, 1.05)\n",
    "\n",
    "# Difference\n",
    "ax3 = fig.add_subplot(1, 3, 3, projection=\"3d\")\n",
    "ax3.set_title(\"Difference between CDFs\")\n",
    "ax3.plot_surface(\n",
    "    mesh_x, mesh_y, real_prob_grid - gen_prob_grid, linewidth=2, antialiased=False, cmap=cm.coolwarm\n",
    ")\n",
    "ax3.set_zlim(-0.05, 0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "name": "#%% md\n"
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   "source": [
    "## 7. Conclusion\n",
    "\n",
    "Quantum generative adversarial networks employ the interplay of a generator and discriminator to map an approximate representation of a probability distribution underlying given data samples into a quantum channel. This tutorial presents a self-standing PyTorch-based qGAN implementation where the generator is given by a quantum channel, i.e., a variational quantum circuit, and the discriminator by a classical neural network, and discusses the application of efficient learning and loading of generic probability distributions into quantum states. The loading requires $\\mathscr{O}\\left(poly\\left(n\\right)\\right)$ gates and can thus enable the use of potentially advantageous quantum algorithms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
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       "<h3>Version Information</h3><table><tr><th>Software</th><th>Version</th></tr><tr><td><code>qiskit</code></td><td>1.4.3</td></tr><tr><td><code>qiskit_machine_learning</code></td><td>0.9.0</td></tr><tr><th colspan='2'>System information</th></tr><tr><td>Python version</td><td>3.12.9</td></tr><tr><td>OS</td><td>Windows</td></tr><tr><td colspan='2'>Fri Jul 18 15:10:22 2025 Eastern Daylight Time</td></tr></table>"
      ],
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       "<IPython.core.display.HTML object>"
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      "text/html": [
       "<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of a Qiskit project</h3><p>&copy; Copyright IBM 2017, 2025.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import tutorial_magics\n",
    "\n",
    "%qiskit_version_table\n",
    "%qiskit_copyright"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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